Achieving the Sustainable Development Goals (SDGs) by 2030 will take major transformations of the agricultural sectors of developing economies. These transformations of food and agricultural systems—or delays in carrying them out—will have direct and indirect implications for multiple SDGs. An important first step is overhauling countries’ policy systems and reorienting them towards evidence-based policy making. This is crucial because policy research and the evidence it generates are often not effectively used in the policy making process, even when the evidence may clearly point in a specific direction. What is needed to transform a national policy system so that it can effectively use research-based evidence to achieve the SDGs?

Here, I argue that increasing the capacity for translational research—combining a country’s research evidence with the experiences of its policymakers to formulate broad policy prescriptions—is key for the next generation of reforms needed for achieving the SDGs in developing countries.

The lack of local capacity for evidence-based policy making has broad consequences. In many developing countries, research and policy making capacities remain isolated from each other and broader development discussions. External technical assistance generates much of the research evidence. The key issues are not fully understood. The research is not translated into evidence. Global and regional efforts and commitments are not fully integrated into national policies and goals. Even when sound evidence is absorbed into policy and strategy documents, progress towards the SDGs remains slow.

Investing even a fraction of the share of resources typically spent on external technical assistance in building local translational research capacity can make a big difference in these areas. While it’s hardly a linear process, building translational capacity to achieve global goals at the national level is key. This holds irrespective of the sector targeted by the various SDGs—agriculture, food, health, climate change, sustainable energy, or malnutrition.

Here are three examples that illustrate ways this this process could be helpful.

• The Green Revolution in developing countries. Investing in agriculture can yield results beyond food self-sufficiency, including non-farm rural income growth, improved rural employment prospects, and poverty reduction. Yet in many developing countries, agricultural investment remains insufficient; securing needed investments to improve rural infrastructure, research and extension, and food processing sector remains a challenge. This is partly due to the absence of country-level translational research focused on incorporating the SDGs and other global and regional development goals into the national policy making process.
• Agricultural market reforms in Malawi. A parastatal in Malawi—the Agricultural Development and Marketing Corporation (ADMARC)—plays the role of “buyer of the last resort” and of seller in remote areas, ensuring food accessibility. It also plays the role of food price stabilizer in times of scarcity, releasing stored grains and other foods purchased during periods of plenty. It plays a similar role in a geographical sense, buying in an area of surplus and moving the food to an area of food deficit. Yet in Malawi and some other democracies, particularly young ones, ruling parties view these organizations as piggy banks to fund the next election campaign and maintain power. The management of parastatals as an instrument for managing the food economy has not evolved and transformed itself to act independently of politics. Local translational research capacity can help.
• Aquaculture in Nigeria. Recently we studied the aquaculture value chain in the South West region of Nigeria. A major constraint on improving productivity has been the availability of quality broodstock, from which hatcheries produce fingerlings to supply to fish farmers. If the broodstock is of low quality, the breeding of quality fingerlings suffers and with it, productivity. Importing broodstock, however, requires very good infrastructure and regulatory systems. Absent those things, no amount of research on value chain development will help. Translation research can identify such critical obstacles in the development of a sector or a subsector, engaging its actors and players and improving their capacity and institutions.

Several successful cases of progress in the agriculture sector in the last decade show the potential of translational research capacity. In Africa, the policy systems of Ethiopia and Rwanda are generally functioning well thanks to their translational capacity, with research evidence reinforcing action.

Are they outliers, or are there good formulas for transforming country policy systems to function effectively by using research evidence? A common factor is that the leaders of both Ethiopia and Rwanda are committed to agricultural development and keen to adopt models in which agriculture is the engine of growth. The political commitment is in the right place and in good measure. In addition, the countries have improved the public sector capacity to deliver services in the research and extension systems. Finally, they have better coordination mechanisms that marshal needed evidence to support interventions, and they continuously update that information via transformational research capacity, enabling them to fine-tune.

How do we promote translational research capacity for achieving the SDGs? Understanding a country’s policy system and its actors and players is the first step. Then it is important to consider three capacity angles. First, the evidence generated by research and analysis; second, linking that evidence to the policy making process; and third, connecting the policy making process and the evidence to possible impacts on the implementation programs that address SDGs.

Research has shown that even when policy makers fully understand the issues they face, they may not be able to act if the policy system is not strong enough to get the evidence to support them. In addition, research and evidence are necessary but not enough for effective policy adoption. Policy systems must be able to translate research evidence into information that is useful for policy making. If the policy implications of the research are not fully understood, or if the research itself raises doubts, uncertain outcomes may result upon implementation. Then there is less chance of research evidence being translated into policy, let alone implemented.

Social marketing of policy results is important. Building the credibility of local researchers and analysts is key for producing the local evidence necessary for transforming the policy system. Fostering the local capacity for context-specific research, learning lessons from pilot interventions, and ultimately demonstrating the benefits of policy change through effective policy communications will provide more opportunities for adopting and scaling up sound policies.

Communities of players within policy systems should be actively engaging on key priorities. They need the capacity to do that and should be fully informed about the consequences what they promote. For example, local traders in many countries complain about the absence of consistent marketing and trade policies. Yet they often benefit from those very uncertainties when they have inside information on, say, what the government will do next in the maize market. That may help some politically-connected traders, but it also leads to market instability.

Policy makers will accept some policy changes more easily than others. For example, in Kenya there was little resistance to introducing broadband technology to enable farmers to use mobile phones for online banking. Yet technology policies related to seed industry regulation and the introduction of GMOs remain more contentious. Crises also influence institutional attitudes towards policy innovation. For example, Azerbaijan’s oil crisis over the last decade helped boost promotion of other exports including food, resulting in major policy and institutional innovations in food safety and standards. Yet broader policy reforms—such as ending wasteful fertilizer subsidies—may take a long time, even when there is ample research evidence of their benefits.

Developing effective translational research capacity requires a new generation of researchers who base their priorities on the information needs of policy makers and can integrate their results into the policy process. Policy makers need proof of concept before they jump in and use the evidence. This requires evidence based on the history of implementation, and that in turns requires that researchers be independent and credible.

Mentoring a new generation of researchers and analysts who can develop trust and build credibility with policy makers is key for developing local translational capacity. Guiding institutions on how to use information from research effectively is also important. Translational research brings the researcher’s ability to generate evidence face to face with the operational needs of policy makers. It helps in the process of scaling up innovations—whether technological, institutional, or policy-related.

Finally, communication is a key element of translational research. Policy briefs calling for action should draw on peer-reviewed publications, and context-specific policy advice should be based on research. Effective policy communication requires an informatics approach that tracks both research and outreach activities.

In summary, research evidence, institutional capacity, and policy engagement are the three pillars of a system that enables effective policy change. Yet in many developing countries, current approaches to academic research and policy communications stand in the way of transforming policy systems and the adoption of policies for achieving the SDGs. Developing translational research and the capacity for getting from policy research to policy action can break this logjam.

Suresh Babu is Head of Capacity Strengthening and a Senior Research Fellow at IFPRI.